DBMS > RavenDB vs. SiriDB vs. Spark SQL vs. Transbase vs. VelocityDB

System Properties Comparison RavenDB vs. SiriDB vs. Spark SQL vs. Transbase vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Open Source Operational and Transactional Enterprise NoSQL Document Database

Open Source Time Series DBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Document store

Time Series DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#16	Object oriented DBMS

Website

ravendb.net

siridb.com

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

velocitydb.com

Technical documentation

ravendb.net/docs

docs.siridb.com

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

velocitydb.com/UserGuide

Developer

Hibernating Rhinos

Cesbit

Apache Software Foundation

Transaction Software GmbH

VelocityDB Inc

Initial release

2010

2017

2014

1987

2011

Current release

5.4, July 2022

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

7.x

License

Commercial or Open Source

Open Source

AGPL version 3, commercial license available

Open Source

MIT License

Open Source

Apache 2.0

commercial

free development license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C and C++

Server operating systems

Linux
macOS
Raspberry Pi
Windows

Linux

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (RQL)

SQL-like DML and DDL statements

yes

APIs and other access methods

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

.Net

Supported programming languages

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID, Cluster-wide transaction available

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Authorization levels configured per client per database

simple rights management via user accounts

fine grained access rights according to SQL-standard

Based on Windows Authentication

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